At a Glance
- Tasks: Design and develop scalable data models using Snowflake and dbt to support analytics.
- Company: Join Wood Mackenzie, a global leader in energy analytics and insights.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on continuous learning and innovation.
- Why this job: Make an impact by transforming data into actionable insights for global energy leaders.
- Qualifications: Bachelor’s degree in a quantitative field and 2-4 years of relevant experience.
The predicted salary is between 45000 - 55000 € per year.
Wood Mackenzie is the global leader in analytics, insights and proprietary data across the entire energy and natural resources landscape. For over 50 years our work has guided the decisions of the world’s most influential energy producers, utilities companies, financial institutions and governments. Now, with the world’s energy system more complex and interconnected than ever before, sector-specific views are no longer enough. That’s why we’ve redefined what’s possible with Intelligence Connected.
By fusing our unparalleled proprietary data with the sharpest analytical minds, all supercharged by Synoptic AI, we deliver a clear, interconnected view of the entire value chain. Our trusted team of 2,700 experts across 30 countries breaks siloes and connects industries, markets and regions across the globe. This empowers our customers to identify risk sooner, spot opportunities faster and recalibrate strategy with confidence – whether planning days, weeks, months or decades ahead.
Role Purpose
A new Analytics Engineer position is being created to enhance the data team's capabilities in managing and transforming data within the Snowflake data platform using dbt (data build tool). This role will be pivotal in building a scalable and reliable data infrastructure to support analytics and data-driven decision-making across the business. The Analytics Engineer will act as a bridge between data engineers and data analysts, applying software engineering best practices to the analytics workflow. This includes developing, testing, and deploying data models, as well as ensuring data quality and creating robust documentation.
Key Responsibilities:
- Data Modelling and Transformation: Designing, developing, and maintaining scalable and efficient data models and transformation pipelines in Snowflake using dbt.
- Workflow Management: Building and managing data transformation workflows, ensuring data is timely, accurate, and ready for analysis.
- Data Quality and Governance: Implementing data quality tests and documentation to ensure the reliability and trustworthiness of the data. This includes supporting data governance and quality assurance activities.
- Collaboration: Working closely with data analysts, data engineers, and business stakeholders to understand data requirements and deliver actionable insights. The role involves engaging directly with stakeholders and building their confidence in data-driven outcomes.
- System Optimisation: Identifying opportunities to improve data processes, optimise performance, and ensure the scalability of the data platform.
- Technical Expertise: Acting as a subject matter expert on dbt and Snowflake, providing guidance and best practices to the wider data team.
Candidate Profile:
The ideal candidate will possess a strong technical background combined with excellent analytical and communication skills.
Essential Experience and Qualifications:
- A Bachelor’s degree in a quantitative field such as Data Science, Computer Science, or a related discipline.
- 2-4 years of hands-on experience in a data-focused role, with proven experience in data modeling and transformation.
- Advanced proficiency in SQL for complex querying and data manipulation.
- Demonstrable experience with dbt and cloud data warehouses, particularly Snowflake.
- Proficiency with GitHub and AWS tools such as Step Functions, Athena, and S3.
- Strong discipline in attention to detail, data accuracy, and structured working practices.
- Reliable execution and ownership of deliverables.
- Proactive learner with genuine curiosity for emerging technologies and a commitment to continuous professional development.
Desirable Skills:
- Proficiency in Python for data handling and automation.
- Experience with ETL processes and data integration via APIs.
- Familiarity with data visualization tools such as Power BI or Tableau.
- A strong understanding of data governance frameworks and data security protocols.
- Exceptional problem-solving skills and a high level of attention to detail.
- The ability to translate complex technical concepts for non-technical audiences.
- A collaborative spirit and a commitment to continuous professional development.
This new role is a fantastic opportunity for a data professional passionate about building modern data stacks and enabling organisations to leverage their data assets effectively.
Equal Opportunities
We are an equal opportunities employer. This means we are committed to recruiting the best people regardless of their race, colour, religion, age, sex, national origin, disability or protected veteran status. If you are applying for a role and have a physical or mental disability, we will support you with your application or through the hiring process.
Analytics Engineer II employer: Wood Mackenzie
Wood Mackenzie is an exceptional employer, offering a dynamic work culture that fosters collaboration and innovation among its 2,700 experts across 30 countries. With a strong commitment to employee growth, the company provides ample opportunities for professional development in the rapidly evolving field of data analytics, all while being at the forefront of the energy and natural resources sector. Located in a vibrant environment, employees benefit from a supportive atmosphere that values inclusivity, trust, and a customer-centric approach, making it an ideal place for those seeking meaningful and rewarding careers.
StudySmarter Expert Advice🤫
We think this is how you could land Analytics Engineer II
✨Tip Number 1
Network like a pro! Reach out to current employees at Wood Mackenzie on LinkedIn. Ask them about their experiences and any tips they might have for the interview process. It’s all about making connections!
✨Tip Number 2
Prepare for the technical side! Brush up on your SQL and dbt skills, as you’ll likely face some practical tests. We recommend doing mock interviews with friends or using online platforms to get comfortable.
✨Tip Number 3
Show your curiosity! During interviews, ask insightful questions about the data challenges Wood Mackenzie faces. This shows you’re genuinely interested in the role and ready to contribute to their mission.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re serious about joining the team at Wood Mackenzie.
We think you need these skills to ace Analytics Engineer II
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Analytics Engineer role. Highlight your experience with data modelling, dbt, and Snowflake to show us you’re the right fit!
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about data and how your background makes you a great candidate. Don’t forget to mention your curiosity for emerging technologies – we love that!
Showcase Your Technical Skills:Be specific about your technical expertise in SQL, GitHub, and AWS tools. We want to see how you’ve applied these skills in real-world scenarios, so don’t hold back on the details!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity at Wood Mackenzie!
How to prepare for a job interview at Wood Mackenzie
✨Know Your Tools Inside Out
Make sure you’re well-versed in dbt and Snowflake, as these are crucial for the role. Brush up on your SQL skills too, since complex querying will be a big part of your job. Being able to discuss specific projects where you've used these tools will really impress the interviewers.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled data quality issues or optimised data processes in the past. Wood Mackenzie values a proactive approach, so demonstrating your ability to identify and solve problems will set you apart from other candidates.
✨Communicate Clearly and Confidently
Since you'll be acting as a bridge between data engineers and analysts, practice explaining complex technical concepts in simple terms. This will show that you can effectively communicate with both technical and non-technical stakeholders, which is key for this role.
✨Emphasise Collaboration
Highlight your experience working in teams and collaborating with various stakeholders. Wood Mackenzie values inclusivity and teamwork, so sharing stories about successful collaborations will resonate well with the interviewers.
